If a neural network can do it, then a neural network can do it… so we either have to accept that a neural network can be intelligent, or that no human can be intelligent.
If we accept that human NNs can be intelligent, then the only remaining question is how to compare a human NN to a machine NN.
Right now, the analysis of LLMs shows that they present: human-like categorization, super-human knowledge, and sub-human reasoning. So, depending on the measure, current LLMs can fall anywhere on the scale of “not AGI” to “AGI overlord”. It’s reasonable to expect larger models, with more multimodal training, to become fully “AGI overlord” by all measures in the very near future.
Don’t buy into the techbro nonsense. Just because they’re called “neural networks” does not mean they work the same way the human brain does. We don’t know how the human brain fundamentally processes data so anyone telling you these NNs work in a way that is the same as blowing wind out their ass.
There was this book called “artificial intelligence” we had on CS something like 20 years ago, which started by analyzing in detail how biological neurons worked in the first few chapters… so maybe you’ll call me a “techbro” and just dismiss all I say, or read far enough to understand that these NNs are mimicking the behavior of actual neurons in a human brain.
We can discuss whether the higher level structures and processes are similar and to what degree, or whether the digital models represent the biological versions more or less accurately, but you can’t deny that the building blocks are replicating the human brain behavior at some level, because that’s exactly what they have been designed to do.
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If a neural network can do it, then a neural network can do it… so we either have to accept that a neural network can be intelligent, or that no human can be intelligent.
If we accept that human NNs can be intelligent, then the only remaining question is how to compare a human NN to a machine NN.
Right now, the analysis of LLMs shows that they present: human-like categorization, super-human knowledge, and sub-human reasoning. So, depending on the measure, current LLMs can fall anywhere on the scale of “not AGI” to “AGI overlord”. It’s reasonable to expect larger models, with more multimodal training, to become fully “AGI overlord” by all measures in the very near future.
Don’t buy into the techbro nonsense. Just because they’re called “neural networks” does not mean they work the same way the human brain does. We don’t know how the human brain fundamentally processes data so anyone telling you these NNs work in a way that is the same as blowing wind out their ass.
There was this book called “artificial intelligence” we had on CS something like 20 years ago, which started by analyzing in detail how biological neurons worked in the first few chapters… so maybe you’ll call me a “techbro” and just dismiss all I say, or read far enough to understand that these NNs are mimicking the behavior of actual neurons in a human brain.
We can discuss whether the higher level structures and processes are similar and to what degree, or whether the digital models represent the biological versions more or less accurately, but you can’t deny that the building blocks are replicating the human brain behavior at some level, because that’s exactly what they have been designed to do.